8000 [MRG + 1] Fix ValueError in LabelEncoder when using inverse_transform on unseen labels · Pull Request #9816 · scikit-learn/scikit-learn · GitHub
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[MRG + 1] Fix ValueError in LabelEncoder when using inverse_transform on unseen labels #9816

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Merged
merged 2 commits into from Sep 21, 2017
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[MRG + 1] Fix ValueError in LabelEncoder when using inverse_transform on unseen labels #9816

merged 2 commits into from Sep 21, 2017

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ghost
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@ghost ghost commented Sep 21, 2017

Reference Issue

Fix #9812

@ghost ghost mentioned this pull request Sep 21, 2017
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amueller
amueller reviewed Sep 21, 2017
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looks good to me.

sklearn/preprocessing/label.py
@@ -148,8 +149,9 @@ def inverse_transform(self, y):
check_is_fitted(self, 'classes_')

diff = np.setdiff1d(y, np.arange(len(self.classes_)))
if diff:
raise ValueError("y contains new labels: %s" % str(diff))
if len(diff):
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This len is the fix, right?

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Correct - that's all that was needed to produce a sensible error 😄

sklearn/preprocessing/tests/test_label.py
assert_raises(ValueError, le.inverse_transform, [-1])
le.fit([1, 2, 3, -1, 1])
msg = "contains previously unseen labels"
assert_raise_message(ValueError, msg, le.inverse_transform, [-2])
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I find the organization of the tests a bit weird but not your fault. The test that it actually works if they are present is way at the top of the file.

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Happy to reorganise tomorrow if you are able to give me some pointers - I'm not very familiar with the testing structure of sklearn as this is my first issue.

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it's fine, I think.

@amueller amueller changed the title Fix ValueError in LabelEncoder when using inverse_transform on unseen labels [MRG + 1] Fix ValueError in LabelEncoder when using inverse_transform on unseen labels Sep 21, 2017
@lesteve
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lesteve commented Sep 21, 2017

LGTM, merging, thanks a lot @newey01c!

@lesteve lesteve merged commit c554aad into scikit-learn:master Sep 21, 2017
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This is missing a whats_new entry. I'll pull it into my 0.19.1 branch and write an entry there

@jnothman jnothman added this to the 0.19.1 milestone Sep 24, 2017
@ghost ghost deleted the patch_9812 branch September 25, 2017 08:01
maskani-moh pushed a commit to maskani-moh/scikit-learn that referenced this pull request Nov 15, 2017
@maskani-moh
[MRG + 1] Fix ValueError in LabelEncoder when using inverse_transform…
9985b80 
… on unseen labels (scikit-learn#9816)
jwjohnson314 pushed a commit to jwjohnson314/scikit-learn that referenced this pull request Dec 18, 2017
[MRG + 1] Fix ValueError in LabelEncoder when using inverse_transform…
35f2151 
… on unseen labels (scikit-learn#9816)
@ghost ghost mentioned this pull request Dec 27, 2017
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@jnothman jnothman mentioned this pull request Jan 10, 2018
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@svadali16 svadali16 mentioned this pull request Jan 30, 2018
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@qinhanmin2014 qinhanmin2014 mentioned this pull request Jan 31, 2018
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@vdaita
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vdaita commented Feb 3, 2018 •
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The issue appears to be persistent - I am using LabelEncoder. Here is my stack trace:

 File "ann.py", line 71, in <module>
    X_train, X_test, y_train, y_test = get_dataset("Churn_Modelling.csv", 3, 13, 13)
  File "ann.py", line 28, in get_dataset
    encoder.fit(labels)
  File "/home/yolopc/.local/lib/python3.5/site-packages/sklearn/preprocessing/label.py", line 96, in fit
    self.classes_ = np.unique(y)
  File "/home/yolopc/.local/lib/python3.5/site-packages/numpy/lib/arraysetops.py", line 210, in unique
    return _unique1d(ar, return_index, return_inverse, return_counts)
  File "/home/yolop
8000
c/.local/lib/python3.5/site-packages/numpy/lib/arraysetops.py", line 277, in _unique1d
    ar.sort()
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Do you have any suggestions?

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jnothman commented Feb 3, 2018

As noted in #10552, this was accidentally not included in the 0.19.1 release. Using the development version of scikit-learn will make it work.

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vdaita commented Feb 4, 2018 via email

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jnothman commented Feb 4, 2018 via email

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vdaita commented Feb 5, 2018 via email

@ayashjorden ayashjorden mentioned this pull request Mar 10, 2018
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@ianozsvald ianozsvald mentioned this pull request Aug 12, 2018
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@lesteve @jnothman @vdaita @amueller @charlienewey
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